|Publication number||US20110009720 A1|
|Application number||US 11/982,565|
|Publication date||13 Jan 2011|
|Filing date||2 Nov 2007|
|Priority date||2 Nov 2006|
|Publication number||11982565, 982565, US 2011/0009720 A1, US 2011/009720 A1, US 20110009720 A1, US 20110009720A1, US 2011009720 A1, US 2011009720A1, US-A1-20110009720, US-A1-2011009720, US2011/0009720A1, US2011/009720A1, US20110009720 A1, US20110009720A1, US2011009720 A1, US2011009720A1|
|Inventors||Kislaya Kunjan, Frank Perry Lloyd|
|Original Assignee||Kislaya Kunjan, Frank Perry Lloyd|
|Export Citation||BiBTeX, EndNote, RefMan|
|Patent Citations (4), Non-Patent Citations (6), Referenced by (13), Classifications (26), Legal Events (3)|
|External Links: USPTO, USPTO Assignment, Espacenet|
This application makes reference to Provisional Application 60/856,456, filed on Nov. 2, 2006.
1. Field of the Invention
This invention relates generally to the measurement of biological parameters through spectroscopy; and more particularly, the invention relates to measurement of glucose using mid-infrared spectroscopy.
2. Description of Related Art
Recent medical studies have made it overwhelmingly clear that tight control of blood glucose levels of patients in critical care settings result in significant improvement in health outcomes. The adverse effect of hyperglycemia on hospital length of stay, morbidity, and mortality is substantial. Consequently, there is a nationwide pursuit of implementing improved glycemic control in both diabetic and non-diabetic hospitalized patients. At the core of tight glycemic control by intensive insulin therapy is frequent and accurate glucose monitoring. Part of the pursuit has focused on using infrared spectroscopy. Researchers realize that the mid-infrared region is very well suited for biological sensing due to its unique specificity for identifiable molecules of interest. Until recently, work in this region was limited due to lack of high powered light sources.
Infrared (IR) Spectroscopy has been the most active area in non-invasive and minimally invasive monitoring research. A lot of interest was generated by this technology many years ago when it was found that IR waves could be used to directly measure glucose. A brief background on the science of spectroscopy is now provided.
Spectroscopy is the use of the absorption, emission, or scattering of electromagnetic radiation by matter to qualitatively or quantitatively study matter or to study physical processes. Matter can be atoms, molecules, atomic or molecular ions, or solids and it can capture electromagnetic radiation and convert the energy of a photon to internal energy. Energy is transferred from the radiation field to the absorbing species. The energy change of the absorber can be described as a transition or an excitation from a lower energy level to a higher energy level.
Measuring the concentration of an absorbing species in a sample is accomplished by applying the Beer-Lambert law. The Beer-Lambert law defines a linear relationship between absorbance and concentration of an absorber of electromagnetic radiation. Assuming that the absorbance of a particular analyte is overlapped by absorbance from other constituents, the general form of the Beer-Lambert law is usually written as:
A=ΣεiCiL, Equation 1:
Where A is the absorbance, C is the molar absorptivity, C is the concentration of the constituent, L is the optical path length and the subscript ‘i’ corresponds to the constituent in the absorbing compound. The expression relating the concentration to IR absorption intensities then takes the following expanded form:
C i =K 0i +K 1i A(λ)1 +K 2i A(λ)2 + . . . +K Ni A(λ)N, Equation 2:
where KNi are the calibration coefficients for the ith constituent, and λN are the corresponding analytical wavelengths.
Experimental measurements are usually made in terms of transmittance (T).
A=−log(T)=−log(I/I 0), Equation 3:
where I and Io represent light intensities before and after passing through the sample of path length ‘L’. The attenuation in intensity can be evaluated as a function of wavelength in order to extract information from the spectrum concerning the presence of the analyte in the sample (
Various optical techniques for glucose measurement, currently under development involve near infrared spectroscopy, mid-infrared spectroscopy, ram an spectroscopy, photo-acoustic spectroscopy, and scatter and polarization changes. Some of the daunting challenges posed by these techniques include weak optical signals, biochemical interference, and patient-to-patient variability. The mid-infrared and near infrared regions are relatively more useful in monitoring of analytes such as glucose.
The high initial cost of implementing mid-infrared technology can be overcome with widespread commercial applications. In particular, applications that place a premium on sensitivity, specificity and overall system accuracy, the spectral region of choice is the mid-infrared. Thus far, mid-infrared spectroscopy based systems have not been implemented in a clinical setting.
Substances such as glucose have covalent bonds with fundamental resonance frequencies in the mid-infrared region of the light spectrum, i.e., at frequencies corresponding to infrared light wavelengths from 2.5 to 25 μm. Hence, the mid-infrared region of the absorption spectrum of such analytes contain relatively narrow absorption lines specific to each individual substance. Infrared spectroscopic technologies measure blood analyte levels (such as blood glucose levels) by measuring light absorption when an infrared spectrum is transmitted through a sample. Every chemical entity absorbs infrared light in a unique way, so every chemical entity has its own particular infrared spectrum. Moreover, the absorption of light is directly proportional to the concentration of the particular chemical entity in the test sample. Because each analyte (such as glucose) has its own unique infrared spectrum, it can be identified and measured. A glucose molecule belongs to the class of carbohydrates with atoms C, H and O in the ratio of 1:2:1. The strongest absorption bands involve stretching of the C—O bonds of COH and COC groups.
Glucose has fundamental absorption bands in the 9-10 μm region. Factors to consider when selecting which wavelength bands to use to measure glucose in biological fluid may include:
The measurement of blood glucose by any technique is inherently complex because of the wide range of potentially interfering components. For a noninvasive technique, not only are there many analytes within human blood that could interfere with the measurement (including the highly absorbing nature of water), but there are also other problems such as the variability, lack of homogeneity of human skin and the constantly changing human physiology. Present methods for monitoring blood glucose levels either require frequent physical sampling of the blood through finger pricks or manual blood removal from a vein using a syringe. Non-invasive optical methods under development do not require physical contact of the sample with the sensing element. However, these methods face serious challenges with regard to specificity and therefore measurement accuracy. Alternate measuring devices utilize subcutaneously implanted sensors to determine glucose levels in the interstitial fluid space. These measurements however suffer from an inherent time lag with the glucose levels in the blood, and associated inaccuracies. There continues to be an unmet need for an automated continuous “blood“glucose monitoring system that is accurate in the critical care settings.
Further, as disclosed in U.S. patent application Ser. No. 10/692,996 to Gore et al. (the “Gore Application”), the use of mid-infrared electromagnetic radiation may be used to sense glucose levels in ultrafiltered blood. Ultrafiltration is a variety of membrane filtration in which hydrostatic pressure forces a liquid against a semipermeable membrane, whereby suspended solids and solutes of high molecular weight (e.g. large protein molecules) are retained, while water and low molecular weight solutes (such as glucose) pass through the membrane. The latter can then be used for analysis. However, using the technique disclosed in the Gore Application has proven difficult in a clinical setting due to problems with their ultrafiltrate harvesting method and the low sensitivity of the system. The low sensitivity in part is due to their use of low powered thermal light sources and therefore having to contend with a low optical path length because that is the only way to perform any measurement in the water window of the mid-infrared spectrum. Additionally, reduction of noise from this method required use of cryogenically cooled detection apparatus that is bulky, and cumbersome. Further, as with many other glucose monitors utilizing optical methods, the method disclosed in the Gore Application works with only ultrafiltered blood products, as whole blood contains a number of cellular components that have made it very difficult to reproduce accurate readings. Further, U.S. Pat. No. 6,737,351 to Lendl et al. (the “Lendl Patent”) describes the use of mid-infrared quantum cascade laser for biological measurements, but does not disclose any method to carry out direct analytical measurements in whole blood samples.
Absorbance spectroscopy measurements can be carried out through two common modes, namely transmittance and reflectance or Attenuated Total Reflection (ATR). In the ATR mode light undergoes total internal reflection and an evanescent light wave penetrates into the sample. The absorption which thereby occurs leads to an attenuation of the intensity of the light transported. This attenuation in intensity can be evaluated as a function of wavelength in order to extract information from the spectrum concerning the presence of the analyte in the sample. For ATR measurement on whole blood, protein deposition on the surface of the crystal is a significant problem. Additionally, it has often been difficult to attain a high pathlength in an ATR mode. These shortcomings can be overcome in the transmission mode.
Blood contains about 45% cellular components including erythrocytes, leukocytes, and platelets; the remaining 55% are contributed by water and dissolved solids (3% of the total). Scientific studies have described the feasibility of whole blood based glucose measurement using the laboratory based Fourier Transform Infrared (“FTIR”) spectrometer. However, issues related to the bulky instrumentation, operational handling, fluidics and the optical scattering due to the blood cells have precluded the commercial adaptation of FTIR instruments for automated clinical analysis. In the past, high intensity lead salt lasers in the mid-infrared fingerprint region were bulky, required cryogenic cooling and were not explored for bio-sensing applications. In FTIR spectrometry, the incandescent light source behaves like a black body source and the optical path length through a sample must be in the low micrometer range (typically between 10-50 μm) in order to perform measurements in the finger print region. The short optical path length is a serious limitation on the sensitivity and therefore to achieve higher sensitivity, a higher intensity light source is highly desirable.
Given the state of the prior art the present invention has the following objectives:
measure venous blood glucose levels of patients in critical care settings in an automated fashion;
overcome the drawbacks associated with incandescent light sources;
discover the ideal mid-infrared path length which allows for resolvable differences between physiological concentrations of the analyte, such as glucose;
develop a sophisticated approach for estimating analyte concentrations in a complex mixture, such as whole blood using mid-infrared spectroscopy;
derive a technique to accurately find the optimal set of wavelengths in a spectral region, particularly for complex specimens where many wavelength terms may be required;
design a mid-infrared monitor that can be implemented in a clinical setting;
resolve the common problems experienced in the-prior art in using ATR and FTIR in the mid-infrared region in attempting to monitor glucose in a clinical setting;
invent a convenient and less intrusive technique for continuously extracting whole blood samples from a patient in a ICU setting;
devise a convenient method for calibrating the system yielding accurate results for individual patients; and
produce a monitor meeting the foregoing objective, is cost effective to implement in a clinical setting that operates at room temperature, does not require cryogenic cooling, is not bulky and cumbersome to operate, nor occupies a lot of space.
Therefore, in light of the foregoing, a blood glucose monitor that can continuously monitor the blood glucose levels of an ICU patient in an automated fashion, using venous whole blood as the sample medium would be greatly appreciated in the art. It may be noted here that the term continuous as used through out this application refers to a fluid sampling and glucose testing frequency that ranges from few seconds to several minutes between measurements. The use of a similar device utilized for sensing other blood analytes would be further appreciated.
The present invention provides a system and method for monitoring glucose levels in whole blood and other biological fluids like plasma or ultrafiltrate in patients, wherein blood glucose is monitored from whole blood samples taken automatically at predetermined intervals and tested utilizing mid-infrared spectroscopy. Non-ionic surfactants are utilized to homogenize samples through cell lysis, thereby allowing the use of unfiltered whole blood to be used, and providing for automated sensing using mid-infrared laser technology that can fit well within an intensive care unit.
Other objects and advantages of the present invention will be readily apparent upon a reading of the following brief descriptions of the drawing figures, detailed descriptions of preferred embodiments of the invention, the appended claims and drawings.
The above mentioned and other objects and features of this invention and the manner of attaining them will become apparent, and the invention itself will be best understood by reference to the appended drawings. In the course of the following detailed description, reference will be made to the appended drawings in which:
In the following description, like reference characters designate like or corresponding parts throughout the several views. Referring now to the drawings in detail, reference is made to
The system comprises a fluidic system comprising a peristaltic pump 32, a demountable transmission based flow-cell (also transmission cell) 33, and a single lumen peripheral intravenous blood access catheter 40 for transmitting a whole blood sample 11 from a patient's peripheral vein (not shown) to the flow-cell 33, as in
The system comprises a module 23 including a Gated Integrator (not shown), Boxcar Averager (not shown), and External Frequency Doubler for Active Baseline Subtraction (not shown). The signal from the integrated detector package 29 is fed to a Gated Integrator and Boxcar Averager System. The Gated Integrator/Boxcar Averager (hereafter referred to as the GI) is designed to recover fast, repetitive, analog signals. In the preferred embodiment, a time “gate” (not shown) of predetermined width is precisely positioned relative to the external trigger (provided from the laser driver) to coincide with the detector 30 sensor, which converts the electromagnetic radiation signal 16 to an electronic analog signal (not shown). The GI amplifies and integrates the analog signal that is present during the time the gate is open, ignoring noise and interference that are present at other times. The integrated signal 29 is then fed to a Boxcar Averager, which averages the output of the gated integrator over many shots from the laser 21.
Since any electromagnetic radiation signal, 16 present during time the gate is open, will add linearly, while noise will add in a “random walk” fashion as the square root of the number of shots, averaging N shots will improve the signal-to-noise ratio by a factor of the square root of N. In addition to using the averaging feature of the GI module, a unique Active Baseline Subtraction (ABS) module (not shown) is used which allows for actively canceling baseline drift. This overall method of signal processing is superior to the methods used by all prior researchers working on QCL based systems. Most use a lock-in amplifier module with or without an optical chopper. This is a sub-optimal solution for recovering fast analog signal from noisy backgrounds that is often typical of room-temperature QCLs. The output 26 from the GI module is read through a Data Acquisition Device (DAQ) device and processed using an algorithm 27. The algorithm continuously acquires and processes the data. After an initial calibration, the software displays the glucose read-out 28 on a real-time basis.
In its simplest form, the calibration problem for optical glucose measurement can be stated as: Given a set of optical measurements and corresponding glucose concentrations, develop a model which will allow prediction of glucose concentration based on analysis of future similar optical measurements. In the preferred embodiment, a single fixed QCL laser wavelength, specific to glucose has been implemented as a starting point. The univariate model is of the following form:
C Glucose =K 0 +K 1. A 9.65 μm Equation 1:
where Ki are the calibration coefficients and A9.65μm is the absorbance of the whole blood sample at 9.65 μm. The coefficients were determined by a two point calibration, i.e. by calculating absorbance of only the high end of the blood glucose concentration with reference to a blank. Linearity was assumed in the glucose concentration range of 0-500 mg/dl, by the use of the strongest analyte absorption band. Elaborate experimental studies using a variety of potential interferents have been performed by the applicant and the absorbance at 9.65 μm was highly specific to glucose.
Still referring to
The applicant derived the optimal path length 14 (
In the vast majority of cases, infrared-based analytical methods are developed via calibration to accepted reference analyses. Calibration therefore derives a model which can recover quantitative analytical information from the infrared spectra. Although this step is a trivial one for very simple (one or two component) systems, more complex mixtures (matrix) require a more sophisticated approach.
The general procedure is the same regardless of the details of the process. The first stage is to accumulate both infrared spectra and assays for a set of appropriate clinical specimens. Ideally, this set of calibration samples should span the range of concentration expected both for the analyte of interest and for any interfering species (i.e. any absorber other than the target compound). Separate calibration models are then developed for each of the target analytes. Finally, each of the calibration models is validated by comparing infrared-predicted levels to the reference levels determined for an independent set of test specimens.
The three of the more common techniques are: multi-wavelength linear regression (MLR), principal component regression (PCR) and partial least squares (PLS). The MLR technique is an extension of Beer's law to include multiple wavelengths and has been described earlier (Equation 2). While simple and powerful, this technique is not guaranteed to find the optimal set of wavelengths in a spectral region, particularly for complex specimens where many wavelength terms may be required, such as for whole blood.
The feature common to both PCR and PLS approach is that each spectrum is reduced to a sum of pseudo-spectra, or “loading vectors”. Each spectrum is newly represented by a unique set of “scores”—the set of coefficients required to reconstruct the original spectrum from the set of loading vectors. Typically 5-15 loading vectors replace the thousands of intensity values in the original spectra. These scores then provide the basis for quantitation. The essential relationship in both the PCR and PLS models take the form of:
A=TB+EA Equation 4:
With m spectra in the calibration set, each having n absorbance values, A is the m×n matrix of the calibration spectra. The spectra are reconstructed as a product of B (h×n), the new basis set of loading vectors, and T (m×h), the scores. The key to the process is that each spectrum is reduced from a vector of length n (a row in A) to a new vector of length h (the corresponding row in T), where h is typically between 5 and 15. EA corresponds to the spectral residuals. The column matrix of concentration c is also related to the loading vectors T, according to:
c=Tv+e c Equation 5:
Here, v is the matrix of coefficients that relates the scores to the concentrations.
The selection of appropriate optical, fluidic and electronic components and their operating characteristics has been relevant in the successful development of this system. Monitor characterization had involved identifying the laser 21 and its operating conditions (such as pulse frequency, duty cycle, power and temperature of the thermoelectric cooler 31), evaluating the performance of the photoconductive detector in terms of detectivity and noise characteristics, determination of SNR (signal to noise ratio) for the dynamic range of glucose, determination of the appropriate optical path length 14 for maximum sensitivity, and assessment of wavelength requirements.
The recent commercial availability of mid-infrared quantum cascade lasers (QCL) have changed the landscape of potential mid infrared based sensing applications. The QCLs can be operated at room temperature (without cryogenic cooling) conditions and have orders of magnitude better performance in terms of optical power and efficiency than traditional black body sources as in FTIR spectrometers.
A QCL is a unipolar semiconductor laser where light generation is based on intersubband transitions within the conduction band (or valence band). In contrast, conventional semiconductor lasers are bipolar devices where the light generation is based on the recombination of electrons from the conduction band and holes from the valence band across the band gap. Therefore, while the semiconductor material determines the laser wavelength, most common being AlGaAs semiconductors, the emission wavelength of a QCL is determined by the thickness of the alternating layers of different semiconductor materials. The QCLs can be mass-produced leading to inexpensive products.
QCLs have successfully been used for gas absorption measurements and photo-acoustic spectroscopy. In liquid phase, a room temperature QCL can operate with optical path lengths 14 of more than 100 μm, even in the case of aqueous matrices. Furthermore, using room temperature QCLs the signal-to-noise ratio was improved by a factor of 50 compared to state-of-the-art FTIR spectrometers.
High absorbency due to the presence of hemoglobin (100 times higher concentration than glucose), in addition to high water absorption in the mid-infrared region, turns out to be advantageous in laser based spectroscopic analysis because only micro-liters of blood are required to form a thin film of liquid in the sampling cell. Thus, by utilizing a transmission cell 33, referring to
However, in order to keep a constant film 11 in the transmission cell 33, it has been found that a non-ionic surfactant (not shown) must be added to the whole blood sample 11 at a concentration range of about 0.1%-10% to reduce the surface tension and to lyse red blood cells and other cells that can cause noise in the reading due to optical instabilities. Examples of such surfactants include, Triton X-100 and Saponin. Referring now to
One end of the catheter 40 is inserted into a patient's peripheral vein, the other catheter 40 end is connected to the surfactant-saline supply 50, one end of the tube 84 is connected to the surfactant and saline supply 50, the other ends of the catheter 40 and the tube 84 are connected to the mixer 41 and pump 32, which carries fixed and metered amounts of the blood sample mixed with fixed and meter ed amounts of the surfactant-saline supply 50 through the transmission cell 33. Another advantage of a higher intensity light source is the ability to channel the light through a fiber optic system with high efficiency. Other advantages of QCLs in this invention include their small size, possibility for hybrid integration, narrow wavelength selectivity due to spectral line width and mechanical robustness. A tunable QCL can be used for simultaneous detection of multiple analytes, which have characteristic absorption in the mid-infrared spectral region.
While whole blood is preferred as the bodily fluid, as described, other fluids include plasma, serum (i.e. cell free blood) and blood ultrafiltrate (i.e. cell and large protein fi-ee). Blood serum is blood plasma from which clotting factors have been removed. There are various methods for continuous extraction of plasma and ultrafiltrate from whole blood. Neither of these methods would require sample homogenization by cell lysis as described for whole blood. One possible Plasma Extraction Method would be to employ a porous membrane to harvest roughly half of the serum-plasma from the patient blood sample in a flow by operation where the filter membrane comprises the walls of a flow channel continuously extracting serum-plasma, while the blood flows on its way to the waste container. Then the plasma sample is interrogated. Membrane geometry and the differential pressure across the membrane must be controlled to harvest sufficient plasma for measurement while leaving enough to avoid plugging of the membrane. Plugging of the membrane by blood cells must be avoided or accommodated by controlled back flush of plasma. Flow rate of plasma must be sufficient to minimize lag time between blood withdrawal and glucose measurement.
As to utilizing a suitable Ultrafiltration extraction method, Ultrafiltrate may be obtained from the subcutaneous space saline using ultrafiltration fibers available from Bioanalytical System, IN. However, because of the time associated with interstitial fluid and the travel time, this system is not suitable for use in hospitals. A better approach would be to obtain ultrafiltrate samples derived directly from vascular system. Hemofiltration is a well known method to obtain ultrafiltrate.
Referring now to
One end of the catheter is inserted into a patient's peripheral vein. One end of the tube 84 is connected to the surfactant-saline supply 50. The other ends of the catheter and the surfactant-saline supply 50 are connected to the mixer 41 and pump 32. The pump 32 carries fixed and metered amounts of the blood sample mixed with fixed and metered amounts of the surfactant-saline supply 50 through the transmission cell 33. The light transmits from the laser 21 through the first transmission probe 60 through the flow cell 33, through the second transmission probe 61 to the detector 30.
Referring again to
Various proof-of-principle studies have been performed on the preferred embodiment of the quantum cascade laser based sensor system. The idea was to simulate real life conditions by monitoring changes in the glucose specific signal while continuously pumping randomly selected glucose-doped samples through the flow-cell. The sample matrix was made progressively complex from serum to whole blood. A clinically relevant dynamic range of 0-500 mg/dl was selected to monitor the real-time sensor response. The results clearly show that the sensor prototype can accurately resolve clinically relevant changes in glucose concentration with high sensitivity over the entire dynamic range.
Referring now to
While the invention has been disclosed in preferred forms, it will be apparent to those skilled in the art that many modifications, additions, and deletions may be made therein without departing from the spirit and scope of the invention as set forth in the following claims.
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|U.S. Classification||600/316, 600/581, 604/6.04, 600/310, 604/6.09|
|International Classification||A61B5/15, A61M1/38, A61M1/34, A61B5/00|
|Cooperative Classification||A61M2205/7554, A61M1/34, A61B5/1455, A61M2205/3313, A61M1/38, A61M2230/201, A61M1/3496, A61B5/14532, A61B5/1427, A61B5/155|
|European Classification||A61B5/1455, A61B5/145G, A61B5/14B8, A61B5/155, A61M1/38, A61M1/34P, A61M1/34|
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